Next Article in Journal
Control Strategies for Enhancing Frequency Stability by DFIGs in a Power System with High Percentage of Wind Power Penetration
Previous Article in Journal
Effect of Control Measures on Wheel/Rail Noise When the Vehicle Curves
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(11), 1145; doi:10.3390/app7111145

Analysis of the Macroscopic Behavior of Server Systems in the Internet Environment

1
Graduate School of Information Sciences, Tohoku University, Sendai 9808579, Japan
2
Research Institute of Electrical Communication, Tohoku University, Sendai 9808577, Japan
*
Author to whom correspondence should be addressed.
Received: 23 September 2017 / Revised: 19 October 2017 / Accepted: 3 November 2017 / Published: 6 November 2017
(This article belongs to the Section Computer Science and Electrical Engineering)
View Full-Text   |   Download PDF [3777 KB, uploaded 9 November 2017]   |  

Abstract

Elasticity is one of the key features of cloud-hosted services built on virtualization technology. To utilize the elasticity of cloud environments, administrators should accurately capture the operational status of server systems, which changes constantly according to service requests incoming irregularly. However, it is difficult to detect and avoid in advance that operating services are falling into an undesirable state. In this paper, we focus on the management of server systems that include cloud systems, and propose a new method for detecting the sign of undesirable scenarios before the system becomes overloaded as a result of various causes. In this method, a measure that utilizes the fluctuation of the macroscopic operational state observed in the server system is introduced. The proposed measure has the property of drastically increasing before the server system is in an undesirable state. Using the proposed measure, we realize a function to detect that the server system is falling into an overload scenario, and we demonstrate its effectiveness through experiments. View Full-Text
Keywords: macroscopic behavioral model; variance of fluctuation; behavioral monitoring; management of server systems; empirical study macroscopic behavioral model; variance of fluctuation; behavioral monitoring; management of server systems; empirical study
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Tanimura, Y.; Sasai, K.; Kitagata, G.; Kinoshita, T. Analysis of the Macroscopic Behavior of Server Systems in the Internet Environment. Appl. Sci. 2017, 7, 1145.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top